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	<div class="intro">
		<b>Liang Du</b><a href="pdf/cv_LiangDu_cn.pdf">[中文简历]</a> <a href="#Bio">[Bio]</a>
	</div>
	<div class="intro">
		Liang Du is still an assitant professor at <a href="http://scit.sxu.edu.cn" target="_blank">School of
			Computer and Information Technology</a>, <a href="http://www.sxu.edu.cn" target="_blank">Shanxi
			University</a>.
		<BR>
		He holds a group working on applications with big data and AI technology in <a href="http://dig.sxu.edu.cn"
			target="_blank">Institute of Big Data Science and Industry</a>, lead by
		Prof. <a href="http://www.yuhuaqian.net/" target="_blank">Yuhua Qian</a>.
	</div>
	<div class="intro">
		Email: csliangdu [at] gmail.com, im.duliang[at].qq.com <br>
		Address: 1st Floor, Institute of Big Data Science and Industry, Wucheng Road 92#, Taiyuan, Shanxi,
		China, 030006
	</div>
	<table>
		<!--td> <img src="images/me2014.jpg" width="180"> </td>
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			<BR>

			本页面仍在持续更新中。
			<!--h4><a href="MasterCandidateFAQ.html" target="_blank">2019 硕士招生要求</a></h4-->
			<h3>
				I am looking for highly self-motivated undergraduate students as research interns. Please email me with
				your CV.
			</h3>
		</td>
	</table>

	<hr>
	<h3><a href="#Interest">Interests</a> | <a href="#Education">Education</a> | <a href="#Experience">Work
			Experiences</a> | <a href="#Publications">Publications</a> | <a href="#AcademicServices">Academic
			Services</a> | <a href="#Fundings">Fundings</a> | <a href="#Awards">Awards</a></h3>

	<hr>
	<h2> What's New </h2>
	<ul>
		<li> We got several projects from local companies. </li>
		<li> Aug 2015, our proposal has been accepted by NSFC.
		<li> Aug 2015, we got 1 paper accepted by ICDM 2015.
	</ul>

	<hr>
	<h2><a id=Interest> Research Interests </a></h2>
	I have broader interests in <b>Data Mining, Machine Learning, Big Data Analysis</b>. I am particularly interested in
	the following topics:
	<ul>
		<li> Robust Clustering</li>
		<a href="#ijcai15_rmkkm">IJCAI 2015</a>, <a href="#ijcai15_rmkc">IJCAI 2015</a>, <a href="#ijcai15_rce">IJCAI
			2015</a>, <a href="#ijcai13_rmkkm">IJCAI 2013</a>, <a href="#icdm12_rnmf">ICDM 2012</a>
		<li> Multi-source Integration and Clustering</li>
		<a href="#ijcai15_rmkkm">IJCAI 2015</a>, <a href="#ijcai15_rmkc">IJCAI 2015</a>, <a href="#ijcai15_rce">IJCAI
			2015</a>, <a href="#icdm15_mkted">ICDM 2015</a>
		<li> Clustering Ensemble</li>
		<a href="#ijcai15_rce">IJCAI 2015</a>, <a href="#waim13_ssce">WAIM 2013</a>, <a href="#adma_mgnmf">ADMA 2010</a>
		<li> Feature Selection</li>
		<a href="#kdd15_fsasl">KDD 2015</a>, <a href="#icdm14_rfs">ICDM 2014</a>, <a href="#icdm13_lgdfs">ICDM 2013</a>,
		<a href="#waim13_jfs">WAIM 2013</a>
		<li> Active Learning</li>
		<a href="#aaai15_rpe">AAAI 2015</a>, <a href="#icdm15_mkted">ICDM 2015</a>
		<li> Document Summarization</li>
		<a href="#tkde13_summ">TKDE 2013</a>, <a href="#sdm11_summ">SDM 2011</a>, <a href="#cikm10_summ">CIKM 2010</a>
		<li> Heterogeneous Metric Learning</li>
		<a href="#sdm15_llehml">SDM 2015</a>, <a href="#icdm14_hml">ICDM 2014</a>, <a href="#wise13_hml">WISE 2010</a>
		<li> Collaborative Filtering</li>
		<a href="#dasfaa13_follow">DASFAA 2013</a>, <a href="#adma10_ugpmf">ADMA 2010</a>
		<li> Rank Aggregation</li>

		<div id="htmltagcloud"> <span id="0" class="wrd tagcloud8"><a href="#tagcloud">clustering</a></span> <span
				id="1" class="wrd tagcloud0"><a href="#tagcloud">ensemble</a></span> <span id="2"
				class="wrd tagcloud5"><a href="#tagcloud">factorization</a></span> <span id="3" class="wrd tagcloud7"><a
					href="#tagcloud">feature</a></span> <span id="4" class="wrd tagcloud0"><a
					href="#tagcloud">heterogeneous</a></span> <span id="5" class="wrd tagcloud10"><a
					href="#tagcloud">learning</a></span> <span id="6" class="wrd tagcloud7"><a
					href="#tagcloud">matrix</a></span> <span id="7" class="wrd tagcloud0"><a
					href="#tagcloud">metric</a></span> <span id="8" class="wrd tagcloud0"><a
					href="#tagcloud">multiple</a></span> <span id="9" class="wrd tagcloud0"><a
					href="#tagcloud">nonnegative</a></span> <span id="10" class="wrd tagcloud0"><a
					href="#tagcloud">regularized</a></span> <span id="11" class="wrd tagcloud0"><a
					href="#tagcloud">retrieval</a></span> <span id="12" class="wrd tagcloud7"><a
					href="#tagcloud">robust</a></span> <span id="13" class="wrd tagcloud7"><a
					href="#tagcloud">selection</a></span> <span id="14" class="wrd tagcloud8"><a
					href="#tagcloud">unsupervised</a></span> </div>
	</ul>


	<hr>
	<h2><a name=Education>Education</a></h2>
	<ul>
		<li>Sep. 2007 - Jun. 2013. Ph.D. in Computer Science, Institute of Software, Chinese Academy of Sciences,
			Beijing, China</li>
		<li>Sep. 2003 - Jun. 2007. B.Eng. in Software Engineering, Wuhan University, Wuhan, China.</li>
	</ul>

	<hr>
	<h2><a name=Experience>Work Experience</a></h2>
	<ul>
		<li>Jul. 2014. - Present. Assistant Researcher, Institute of Software, Chinese Academy of Sciences, Beijing,
			China.</li>
		<li>Jul. 2013 - Jul. 2014. Software Engineer, Alibaba Group, Beijing, China.</li>
		<li>Sep. 2007 - Jun. 2013. Doctoral Research, Institute of Software, Chinese Academy of Sciences, Beijing,
			China.</li>
		<li>Apr. 2010 - Apr. 2011. Research Intern, HP Lab China.</li>
	</ul>

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	<hr>
	<h2><a id=Publications>Publications</a></h2>

	<h3><b>Research Highlights: KDD(1), IJCAI(4), AAAI(1), ICDM(6), TKDE(1).</b></h3>

	[<a HREF="https://scholar.google.com/citations?user=YisD9wsAAAAJ&sortby=pubdate" target=_blank>Google Scholar</a>]
	[<a HREF="http://dblp.uni-trier.de/pers/hy/d/Du:Liang" target=_blank>DBLP</a>]

	<h3>Journal and Conference Papers (* = corresponding author)</h3>

	<ol>
		<div id="kdd15_fsasl" class="paper">
			<li>
				Peng Zhou, Yi-Dong Shen, <b>Liang Du</b>, Fan Ye and Xuejun Li. Spectral clustering with distinction
				and
				consensus learning on multiple views data. Knowledge-Based Systems. 2019 [<A
					HREF="pdf/RMKKM-IJCAI-2015.pdf" target=_blank>pdf</A>].
			</li>
		</div>
		<BR>
		<div id="access2019_rmkc" class="paper">
			<li>
				Peng Zhou, Fan Ye, <b>Liang Du</b>. Unsupervised Robust Multiple Kernel Learning via Extracting Local
				and lobal Noises, IEEE Access. 2019.
			</li>
		</div>
		<BR>
		<div id="sdm2019" class="paper">
			<li>
				Peng Zhou, Yi-Dong Shen, <b>Liang Du</b>, Fan Ye. Incremental Multi-view Support Vector Machine. SDM
				2019.
			</li>
		</div>
		<BR>
		<div id="sdm2019" class="paper">
			<li>
				李飞, <b>杜亮*</b>, 任超宏. 基于全局融合的多核概念分解. 计算机应用 2019.
			</li>
		</div>
		<BR>
		<div id="tc2018" class="paper">
			<li>
				Mingyu Fan, Xiaoqin Zhang, <b>Liang Du</b>, Liang Chen, and Dacheng Tao. Semi-supervised learning
				through
				label propagation on geodesics. IEEE transactions on cybernetics 48, no. 5 (2018): 1486-1499. [<A
					HREF="pdf/RMKKM-IJCAI-2015.pdf" target=_blank>pdf</A>][<A HREF="https://github.com/csliangdu/RMKKM"
					target=_blank>codes</A>] .
			</li>
		</div>
		<BR>
		<div id="plosone2018_fsasl" class="paper">
			<li>
				Peng Zhou, Fan Ye and <b>Liang Du*</b>. Spectral clustering with distinction and consensus learning on
				multiple views data. PloS one, 13(12), e0208494. [<A HREF="pdf/RMKKM-IJCAI-2015.pdf"
					target=_blank>pdf</A>].
			</li>
		</div>
		<BR>
		<div id="kdd15_fsasl" class="paper">
			<li>
				Yan Wu, <b>Liang Du</b> and HongHong Cheng. Multi-view K-Means Clustering with Bregman Divergences. In
				International CCF Conference on Artificial Intelligence (pp. 26-38). Springer, Singapore..
			</li>
		</div>
		<BR>
		<div id="kdd15_fsasl" class="paper">
			<li>
				Mingyu Fan, Xiaojun Chang, Xiaoqin Zhang, Di Wang and <b>Liang Du*</b>. Top-k Supervise Feature
				Selection
				via ADMM for Integer Programming. in Proceedings of the Twenty-Sixth International Joint Conference on
				Artificial Intelligence (<b>IJCAI</b>), pages 1646-1653, Melbourne, Australia, August 19-25, 2017.
			</li>
		</div>
		<BR>
		<div id="kdd15_fsasl" class="paper">
			<li>
				胡治国，田中崎，<b>杜亮</b>，关晓蔷，曹峰, IP 网络性能测量研究现状和进展, 软件学报, 2016.10.11,28(1)：105~134
			</li>
		</div>
		<BR>
		<div id="kdd15_fsasl" class="paper">
			<li>
				Hanmo Wang, <b>Liang Du*</b>, Peng Zhou, Lei Shi, YuHua Qian and Yi-Dong Shen. Localized Multiple Kernel
				Experimental Design. in Proceedings of the Fifteenth IEEE International Conference on Data Mining
				(<b>ICDM</b>), pages 201-210, Atlantic City, NJ, USA, November 14–17, 2015. (Regular paper,
				acceptance rate 68/807 = 8.4%).
			</li>
		</div>
		<BR>
		<div id="kdd15_fsasl" class="paper">
			<li>NanNan Gu, MingYu Fan, Di Wang, LiHao Jia and <b>Liang Du</b>. Semi-supervised classification based on
				affine subspace sparse representation. Science in China-Series F: Information Sciences, 2015, To appear.
				[<A HREF="http://info.scichina.com/sciF/CN/abstract/abstract518198.shtml" target=_blank>pdf</A>]
			</li>
		</div>
		<BR>
		<div id="kdd15_fsasl" class="paper">
			<li><b>Liang Du</b> and Yi-Dong Shen. Unsupervised Feature Selection with Adaptive Structure Learning. in
				Proceedings of the 21th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (<b>KDD</b>), pages
				209-218, Sydney, Australia, August 10–13, 2015. (Oral paper, Acceptance rate 159/819 = 19.41%). [<A
					HREF="pdf/FSASL-KDD-2015.pdf" target=_blank>pdf</A>][<A HREF="https://github.com/csliangdu/FSASL"
					target=_blank>codes</A>][<A HREF="pdf/FSASL-KDD-2015-slide.pdf" target=_blank>slide</A>][<A
					HREF="pdf/FSASL-KDD-2015-poster.pdf" target=_blank>poster</A>]
			</li>
		</div>
		<BR>
		<div id="nuro15_efs" class="paper">

			<li>Nannan Gu, Mingyu Fan, <b>Liang Du</b>, Dongchun Ren. Efficient Sequential Feature Selection Based on
				Adaptive Eigenspace Model. <b>Neurocomputing</b>, Volume 161, Pages 199–209, August 2015. [<A
					HREF="pdf/ESFS-Neurocomputing-2015.pdf" target=_blank>pdf</A>]</li>
		</div>

		<BR>
		<div id="ijcai15_rmkkm" class="paper">
			<li><b>Liang Du</b>, Peng Zhou, Lei Shi, Hanmo Wang, Mingyu Fan, Wenjian Wang, Yi-Dong Shen. Robust Multiple
				Kernel K-means Clustering using L21-norm. in Proceedings of the Twenty-Fourth International Joint
				Conference on Artificial Intelligence (<b>IJCAI</b>), pages 3476-3482, Buenos Aires, Argentinean, July
				25-31, 2015. (Oral paper, acceptance rate 575/1996 = 28.8%). [<A HREF="pdf/RMKKM-IJCAI-2015.pdf"
					target=_blank>pdf</A>][<A HREF="https://github.com/csliangdu/RMKKM" target=_blank>codes</A>]</li>
		</div>

		<BR>
		<div id="ijcai15_rmkc" class="paper">
			<li>Peng Zhou, <b>Liang Du*</b>, Lei Shi, Hanmo Wang, Yi-Dong Shen. Recovery of Corrupted Multiple Kernels
				for Clustering. in Proceedings of the Twenty-Fourth International Joint Conference on Artificial
				Intelligence (<b>IJCAI</b>), pages 4105-4111, Buenos Aires, Argentinean, July 25-31, 2015. (Oral paper,
				acceptance rate 575/1996 = 28.8%). [<A HREF="pdf/RMKC-IJCAI-2015.pdf" target=_blank>pdf</A>]</li>
		</div>

		<BR>
		<div id="ijcai15_rce" class="paper">
			<li>Peng Zhou, <b>Liang Du*</b>, Hanmo Wang, Lei Shi, Yi-Dong Shen. Learning a Robust Consensus Matrix for
				Clustering Ensemble via Kullback-Leibler Divergence Minimization. in Proceedings of the Twenty-Fourth
				International Joint Conference on Artificial Intelligence (<b>IJCAI</b>), pages 4112-4118, Buenos Aires,
				Argentinean, July 25-31, 2015. (Oral paper, acceptance rate 575/1996 = 28.8%). [<A
					HREF="pdf/RCE-IJCAI-2015.pdf" target=_blank>pdf</A>]</li>
		</div>
		<BR>

		<div id="sdm15_llehml" class="paper">
			<li>Peng Zhou, <b>Liang Du</b>, Mingyu Fan, and Yi-Dong Shen. An LLE based Heterogeneous Metric Learning for
				Cross-media Retrieval. In Proceedings of the Eleventh SIAM International Conference on Data Mining
				(<b>SDM</b>), pages 64-72, Vancouver, British Columbia, Canda, April 30-May 2, 2015. (Oral paper,
				acceptance rate 72/491 = 14.66%). [<A HREF="pdf/LLEHML-SDM-2015.pdf" target=_blank>pdf</A>]
			</li>
		</div>

		<BR>
		<div id="aaai15_rpe" class="paper">
			<li>Hanmo Wang, <b>Liang Du</b> and Yi-Dong Shen. Convex Batch Mode Active Sampling via alpha-relative
				Pearson Divergence. The Twenty-Ninth AAAI Conference on Artificial Intelligence (<b>AAAI</b>), pages
				3045-3051, Austin Texas, USA, January 25-29, 2015. (Acceptance rate 531/1991 = 26.67%). [<A
					HREF="pdf/rPE-AAAI-2015.pdf" target=_blank>pdf</A>]</li>
		</div>

		<div id="icdm14_hml" class="paper">
			<li>Liang Wu, <b>Liang Du</b>, Bo Liu, Guandong Xu, Yong Ge, Yanjie Fu, Yuanchun Zhou, Jianhui Li and Hui
				Xiong. Heterogeneous Metric Learning with Content-based Regularization for Software Artifact Retrieval.
				The 14th IEEE International Conference on Data Mining (<b>ICDM</b>), pages 610-619, Shenzhen, China,
				December 14-17, 2014. (Regular paper, acceptance rate 71/727 = 9.7%). [<A HREF="pdf/cHML-ICDM-2014.pdf"
					target=_blank>pdf</A>]</li>
		</div>

		<BR>
		<div id="icdm14_rfs" class="paper">
			<li>Lei Shi, <b>Liang Du</b> and Yi-Dong Shen. Robust Spectral Learning for Unsupervised Feature Selection.
				The 14th IEEE International Conference on Data Mining (<b>ICDM</b>), pages 977-982, Shenzhen, China,
				December 14-17, 2014. [<A HREF="pdf/RSFS-ICDM-2014.pdf" target=_blank>pdf</A>][<A
					HREF="http://kingsleyshi.com/codes/RSFS.rar" target=_blank>codes</A>]</li>
		</div>
		<BR>
		<div id="icdm13_lgdfs" class="paper">
			<li><b>Liang Du</b>, Zhiyong Shen, Xuan Li, Peng Zhou and Yi-Dong Shen. Local and Global Discriminative
				Learning for Unsupervised Feature Selection. The 13th IEEE International Conference on Data Mining
				(<b>ICDM</b>), pages 131-140, Dallas, TX, USA, December 7-10, 2013. (Regular paper, acceptance rate
				94/809 = 11.6%). [<A HREF="pdf/LGDFS-ICDM-2013.pdf" target=_blank>pdf</A>]</li>
		</div>
		<BR>
		<div id="wise13_hml" class="paper">
			<li>Jun Deng, <b>Liang Du</b> and Yi-Dong Shen. Heterogeneous Metric Learning for Cross-Modal Multimedia
				Retrieval, The 14th International Conference on Web Information System Engineering (WISE), pages 43-56,
				Nanjing, China, October 13-15, 2013. [<A HREF="pdf/HML-WISE-2013.pdf" target=_blank>pdf</A>]</li>
		</div>
		<BR>
		<div id="ijcai13_rcc" class="paper">
			<li><b>Liang Du</b> and Yi-Dong Shen. Towards robust co-clustering. The 23rd International Joint Conference
				on Artificial Intelligence (<b>IJCAI</b>, pages 1317-1322, Beijing, China, August 3-9, 2013. (Oral
				paper, acceptance rate 195/1473=13.2%). [<A HREF="pdf/RCC-IJCAI-2013.pdf" target=_blank>pdf</A>]</li>
		</div>
		<BR>
		<div id="waim13_jfs" class="paper">
			<li><b>Liang Du</b> and Yi-Dong Shen. Joint clustering and feature selection. The 14th International
				Conference on Web-Age Information Management (WAIM), pages 253-264, Beidaihe, China, June 14-16, 2013.
				[<A HREF="pdf/JCFS-WAIM-2013.pdf" target=_blank>pdf</A>]</li>
		</div>
		<BR>
		<div id="waim13_ssce" class="paper">
			<li><b>Liang Du</b> and Yi-Dong Shen, Zhiyong Shen, Jianying Wang and Zhiwu Xu. A self-supervised framework
				for clustering ensemble. The 14th International Conference on Web-Age Information Management (WAIM),
				pages 253-264, Beidaihe, China, June 14-16, 2013. [<A HREF="pdf/SSCE-WAIM-2013.pdf"
					target=_blank>pdf</A>]</li>
		</div>
		<BR>
		<div id="tkde13_summ" class="paper">
			<li>Xuan Li, <b>Liang Du</b> and Yi-Dong Shen. Update summarization via graph-based sentence ranking. IEEE
				Transactions on Knowledge and Data Engineering (<b>TKDE</b>), May 2013, vol.25, no.5, pages 1162-1174.
				[<A HREF="pdf/QPSUM-TKDE-2013.pdf" target=_blank>pdf</A>]</li>
		</div>
		<BR>
		<div id="dasfaa13_follow" class="paper">
			<li>Liang Wu, Alvin Chin, Guandong Xu, <b>Liang Du</b>, Xia Wang, Kangjian Meng, Yonggang Guo and Yuanchun
				Zhou. Who Will Follow Your Shop? Exploiting Multiple Information Sources in Finding Followers. Database
				Systems for Advanced Applications (DASFAA), pages 401-415, Wuhan, China, April 22-25, 2013. [<A
					HREF="pdf/INITS-DASFAA-13.pdf" target=_blank>pdf</A>]</li>
		</div>
		<BR>
		<div id="icdm12_rnmf" class="paper">
			<li><b>Liang Du</b> Xuan Li and Yi-Dong Shen. Robust nonnegative matrix factorization via half-quadratic
				minimization. In Proceedings of IEEE 12th International Conference on Data Mining (<b>ICDM</b>), pages
				201-210, Brussels, Belgium, December 10-13, 2012. (Regular paper, acceptance rate 81/756=10.7%). [<A
					HREF="pdf/RNMF-ICDM-2012.pdf" target=_blank>pdf</A>]</li>
		</div>
		<BR>
		<div id="adma11_ugpmf" class="paper">
			<li><b>Liang Du</b>, Xuan Li, and Yi-Dong Shen. User Graph Regularized Pairwise Matrix Factorization for
				Item Recommendation, in Proceedings of the 7th International Conference on Advanced Data Mining and
				Applications (ADMA), pages 372-385, Beijing, China, December 18-20, 2011. [<A
					HREF="pdf/UGPMF-ADMA-2011.pdf" target=_blank>pdf</A>]</li>
		</div>
		<BR>
		<div id="admm11_mgnmf" class="paper">
			<li><b>Liang Du</b>, Xuan Li, and Yi-Dong Shen. Cluster Ensembles via Weighted Graph Regularized Nonnegative
				Matrix Factorization, in Proceedings of the 7th International Conference on Advanced Data Mining and
				Applications (ADMA), pages 215-228, Beijing, China, December 18-20, 2011. [<A
					HREF="pdf/WGNMF-ADMA-2011.pdf" target=_blank>pdf</A>]</li>
		</div>
		<BR>
		<div id="sdm11_summ" class="paper">
			<li>Xuan Li, <b>Liang Du</b>, and Yi-Dong Shen. Graph-Based Marginal Ranking for Update Summarization, in
				Proceedings of the 11th SIAM International Conference on Data Mining (<b>SDM</b>), pages 486-497,
				Arizona, USA, April 28-30, 2011. [<A HREF="pdf/QCQP-SDM-2011.pdf" target=_blank>pdf</A>]</li>
		</div>
		<BR>
		<div id="icdm10_imf" class="paper">
			<li>Zhiyong Shen, <b>Liang Du</b>, Xukun Shen, and Yi-Dong Shen. Interval-valued Matrix Factorization with
				Applications, in Proceedings of the 10th IEEE International Conference on Data Mining (<b>ICDM</b>),
				pages 1037-1042, Sydney, Australia, December 14-17, 2010. [<A HREF="pdf/IMF-ICDM-2010.pdf"
					target=_blank>pdf</A>]</li>
		</div>
		<BR>
		<div id="cikm10_summ" class="paper">
			<li>Xuan Li, Yi-Dong Shen, <b>Liang Du</b>, and Chen-Yan Xiong. Exploiting novelty, coverage and balance for
				topic-focused multi-document summarization, in Proceedings of the 19th ACM Conference on Information and
				Knowledge Management (<b>CIKM</b>), pages 1765-1768, Toronto, Canada, October 26-30, 2010. [<A
					HREF="pdf/GreedyS-CIKM-2010.pdf" target=_blank>pdf</A>]</li>
		</div>
	</ol>

	<h3>PhD Thesis</h3>
	<div id="thesis_2013" class="paper">
		<li>Clustering with Robust Nonnegative Matrix Factorization, 2013. (In Chinese) [<A
				HREF=pdf/phd_thesis_liang_du.pdf target=_blank>pdf</A>][<A HREF=pdf/phd_slide_liang_du.pdf>slide </A>]
				</li> </div> <hr>
				<h2><a name=Fundings>Research Fundings</a></h2>
				<ul>
					<div id="thesis_2013" class="paper">
						<li>PI. Research on Multi-sources Big Data Robust Clustering, National Natural Science Fund of
							China, 2016.1 - 2018.12.
						</li>
					</div>
					<div id="thesis_2013" class="paper">
						<li>PI. Research on Robust Feature Selection and Extraction for Big Data Analysis, Open project
							of
							State Key Laboratory of Computer Science, Institute of Software, Chinese Academy of
							Sciences,
							2015.1 - 2016.12.
						</li>
					</div>
					<div id="thesis_2013" class="paper">
						<li>Project member. Research on the Representation, Similarity Measurement and Semantic
							Comprehension of the Internet Big Data. National Basic Research Program of China (973
							Program),
							2014.1 - 2018.12.
						</li>
					</div>
				</ul>

				<hr>
				<h2><a name=Awards>Selected Awards & Honors</a></h2>
				<ul>
					<li>Presidential Scholarship of the Chinese Academy of Sciences 2013.
					<li>Outstanding graduate of Beijing, 2013.
					<li>Outstanding graduate of University of Chinese Academy of Sciences, 2013.
					<li>IEEE ICDM 2012 student travel award, 2012.
				</ul>

				<hr>
				<h2><a name=AcademicServices>Academic Services</a></h2>

				<h3>Journal Reviewer</h3>
		<li> IEEE Transactions on Knowledge and Data Engineering (TKDE).</li>
		<li> WIREs Data Mining and Knowledge Discovery (DMKD).</li>
		<li> Information Sciences.</li>
		<li> Neurocomputing.</li>
		<li> International Journal of Pattern Recognition and Artificial Intelligence.</li>

		<h3>Conference PC Member</h3>
		<li> The International Joint Conference on Artificial Intelligence (IJCAI) 2016.</li>
		<li> The 20th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) 2016.</li>
		<li> The workshop, The DAta mining meets Visual Analytics at big data era (DAVA 2015), on The IEEE International
			Conference on Data Mining (ICDM) 2015.</li>
		<li> The IEEE International Conference on Advanced and Trusted Computing (ATC) 2015.</li>

		<h3>External Reviewer</h3>
		<li> The ACM International Conference on Knowledge Discovery and Data Mining (KDD)
			2010, 2013, 2015.</li>
		<li> The International Joint Conference on Artificial Intelligence (IJCAI) 2011, 2015.</li>
		<li> The AAAI Conference on Artificial Intelligence (AAAI) 2012, 2013, 2015, 2016.</li>
		<li> The ACM Conference on Information and Knowledge Management (CIKM) 2011.</li>
		<li> The International Semantic Web Conference (ISWC) 2010, 2011.</li>
		<li> The Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) 2011, 2012, 2013.</li>
		<li> The Pacific Rim International Conferences on Artificial Intelligence (PRICAI) 2010, 2012, 2014.</li>
		<li> The International Conference on Software Engineering and Knowledge Engineering
			(SEKE) 2010, 2011.</li>

		<hr>
		<h2><a name=Bio>Short Bios</a></h2>

		Liang Du is currently a Lecturer in Shanxi University. Prior to that, he was an assitant researcher in the State
		Key Laboratory of Computer Science, Institute of Software, Chinese Academy of Sciences. During July 2013 and
		July 2014, he was a Software Engineer at Alibaba Group working on the optimization of CPS internet ads. He
		received the B.E. degree in Software Engineering from Wuhan University in 2007, and Ph.D degree in Computer
		Science from Institute of Software at University of Chinese Academy of Sciences in 2013. He has broader
		interests in Data Mining, Machine Learning, and Big Data Analysis. He is particularly interested in the
		following topics: clustering with noise and heterogeneous data, ranking for feature selection, active learning
		and document summarization. He has published more than 20 papers in top conferences and journals, including
		KDD(1), IJCAI(4), AAAI(1), ICDM(6), TKDE(1), SDM(2), CIKM(1). He is the recipient of Presidential Scholarship of
		the Chinese Academy of Sciences in 2013. He is now leading/participating a few national projects such as NSFC
		and the 973 program.
		<BR><BR>
		杜亮，博士，山西大学计算机与信息技术学院讲师。主要研究领域：数据挖掘、机器学习。2007年武汉大学获软件工程学士学位，2013年中国科学院软件研究所计算机科学国家重点实验室获博士学位。2013年7月至2014年7月在阿里巴巴集团担任软件工程师从事计算广告、大数据分析等方面的开发和研究。2014年7月至2015年7月担任中科院软件研究所助理研究员。近年来发表学术论文20多篇，其中多篇论文发表于国际顶级会议和期刊，如：ACM
		KDD(1)、 IJCAI(4)、 AAAI(1)、 IEEE ICDM(6)、 IEEE TKDE(1)、SIAM SDM(2)、ACM CIKM (1)等。同时为IEEE TKDE、ACM TIST、DMKD、
		Neurocomputing、
		IJPRAI等国际期刊以及多次为KDD、IJCAI、AAAI、ISWC、PAKDD、PRICAI等国际会议担任审稿人。曾获中国科学院院长奖、北京市优秀毕业生等奖励。目前，作为核心人员参加973和面上课题各一项，主持NSFC青年基金和中科院软件所开放课题各一项。

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